fescarefine: Refine & Test ML models # Features Scaling # Normalization # Datasets

• Define feature scaling/normalization.
• Create and work with test datasets.
• Articulate how testing models can both improve and harm training.

• To make the concepts relatable, the module uses a fictional scenario:
• A charity is training dogs to rescue hikers trapped in avalanches.
• There's debate over which traits matter most-size, age, etc.
• Historical rescue data is available to guide training decisions.
• Since training is costly, choosing the right dogs is critical.
• This sets up a classic supervised learning problem: using labeled data (dog traits + rescue outcomes) to build a predictive model.